excel-analysislisted

# Excel Analysis ## When to Use - Analyze Excel spreadsheets, create pivot tables, generate charts, and perform - User explicitly invokes `/Excel Analysis` ## When NOT to Use - When the task doesn't match this skill's scope -- check related skills - When a more specialized skill exists for the specific task ## Quick start Read Excel files with pandas: ```python import pandas as pd # Read Excel file df = pd.read_excel("data.xlsx", sheet_name="Sheet1") # Display first few rows print(df.head()) # Basic statistics print(df.describe()) ``` ## Reading multiple sheets Process all sheets in a workbook: ```python import pandas as pd # Read all sheets excel_file = pd.ExcelFile("workbook.xlsx") for sheet_name in excel_file.sheet_names: df = pd.read_excel(excel_file, sheet_name=sheet_name) print(f"\n{sheet_name}:") print(df.head()) ``` ## Data analysis Perform common analysis tasks: ```python import pandas as pd df = pd.read_excel("sales.xlsx") # Group by and aggregate sales_by_region = df.groupby("region")["sales"].sum() print(sales_by_region) # Filter data high_sales = df[df["sales"] > 10000] # Calculate metrics df["profit_margin"] = (df["revenue"] - df["cost"]) / df["revenue"] # Sort by column df_sorted = df.sort_values("sales", ascending=False) ``` ## Creating Excel files Write data to Excel with formatting: ```python import pandas as pd df = pd.DataFrame({ "Product": ["A", "B", "C"], "Sales": [100, 200, 150], "Profit": [20, 40, 30]